Author Manuscript NIH Public Access Naotsugu Tsuchiya ...authors.library.caltech.edu › 74150 › 3 › nihms229915.pdf · Manifestation of ocular-muscle EMG contamination in human

Manifestation of ocular-muscle EMG contamination in humanintracranial recordings

Christopher K. Kovach1,3,4,*, Naotsugu Tsuchiya2,3, Hiroto Kawasaki1, Hiroyuki Oya1,Mathew A. Howard III1, and Ralph Adolphs1,2,41 Department of Neurosurgery, The University of Iowa College of Medicine2 Division of Humanities and Social Sciences, California Institute of Technology3 Brain Science Institute, Tamagawa University, Tokyo, Japan4 Division of Biology, California Institute of Technology

AbstractIt is widely assumed that intracranial recordings from the brain are only minimally affected bycontamination due to ocular-muscle electromyogram (oEMG). Here we show that this is not alwaysthe case. In intracranial recordings from five surgical epilepsy patients we observed that eyemovements caused a transient biphasic potential at the onset of a saccade, resembling the saccadicspike potential commonly seen in scalp EEG, accompanied by an increase in broadband powerbetween 20 and 200 Hz. Using concurrently recorded eye movements and high-density intracranialEEG (iEEG) we developed a detailed overview of the spatial distribution and temporal characteristicsof the saccade-related oculomotor signal within recordings from ventral, medial and lateral temporalcortex. The occurrence of the saccadic spike was not explained solely by reference contact location,and was observed near the temporal pole for small (< 2 deg) amplitude saccades and over a broadarea for larger saccades. We further examined the influence of saccade-related oEMG contaminationon measurements of spectral power and interchannel coherence. Contamination manifested in bothspectral power and coherence measurements, in particular, over the anterior half of the ventral andmedial temporal lobe. Next, we compared methods for removing the contaminating signal and foundthat nearest-neighbor bipolar re-referencing and ICA filtering were effective for suppressing oEMGat locations far from the orbits, but tended to leave some residual contamination at the temporal pole.Finally, we show that genuine cortical broadband gamma responses observed in averaged data fromventral temporal cortex can bear a striking similarity in time course and band-width to oEMGcontamination recorded at more anterior locations. We conclude that eye movement-relatedcontamination should be ruled out when reporting high gamma responses in human intracranialrecordings, especially those obtained near anterior and medial temporal lobe.

Keywordsintracranial EEG; ECoG; saccadic spike; EMG; gamma band; Eye Movement; Eye Muscle

*Correspondence to: Dr. Christopher K. Kovach, 408 MRC, Department of Neurosurgery, University of Iowa Healthcare and Clinics,200 Hawkins Drive, Iowa City, IA 52242, [email protected]'s Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customerswe are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resultingproof before it is published in its final citable form. Please note that during the production process errors may be discovered which couldaffect the content, and all legal disclaimers that apply to the journal pertain.

NIH Public AccessAuthor ManuscriptNeuroimage. Author manuscript; available in PMC 2012 January 1.

Published in final edited form as:Neuroimage. 2011 January 1; 54(1): 213–233. doi:10.1016/j.neuroimage.2010.08.002.

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IntroductionCell-population level signals are important in the study of brain physiology because they indexactivity across many scales of time and anatomy, can be measured non-invasively at the scalpas well as intracranially and can reveal large-scale interactions in the brain (Engel et al.,2005; Lachaux et al., 2006). Recording of such signals has become particularly important inthe diagnosis and clinical evaluation of a number of disorders, such as epilepsy. Yet despitethe clinical and experimental usefulness of such signals, determining their physiological originwith sufficient detail and certainty to address experimental questions (the so-called inverseproblem) remains a significant challenge, given the multitude of possible neural and extra-neural bioelectric sources (Baillet et al., 2001). A sobering reminder that the inverse problemextends well beyond the discrimination of cortical sources is the recent observation that signalsgenerated by the eye muscles during saccades can be mistaken for scalp-EEG activity in thegamma band (Reva and Aftanas, 2004; Trujillo et al., 2005; Yuval-Greenberg et al., 2008).The EMG signal arising from ocular muscle (oEMG), which commonly manifests as the“saccadic-spike potential” in scalp recordings (Becker et al., 1972), can be misinterpreted asa cortical gamma-band responses in averages of spectral power (Yuval-Greenberg et al.,2008). The problem is worsened by the fact that eye movements are correlated with manycognitive processes and cannot be fully controlled through instructed fixation (Engbert andKliegl, 2002). The failure to appreciate the contribution of saccade-related oEMG has castsome doubt on a substantial part of the literature on gamma-band EEG responses in attentionaland perceptual processing (Fries et al., 2008). Such limitations of physiological specificity areovercome using invasive recordings from the brain in patients for which such recordings areclinically justified. Intracranial recordings provide an increasingly important complement toother methods of studying the functional organization of the human brain (Jerbi et al.,2009b). Direct recordings are typically obtained from subdurally implanted electrode stripsand grids (ECoG) or from penetrating depth electrodes implanted in the brain parenchyma. Incontrast to scalp recordings, intracranial recordings have been regarded as comparativelyimmune to oEMG contamination (Fries et al., 2008; Meador et al., 2002; Yuval-Greenberg etal., 2008). This assumption stems from the fact that they are obtained near the generatingcortical sources and from the differing conductive properties of intra- and extra-cranialcompartments.

Recent work has placed some some qualifications on this assumption. In particular Jerbi et al.describe saccadic spikes in data from closely spaced bipolar stereotactic EEG (sEEG) at theimmediate apex of the temporal pole (Jerbi et al., 2009a). The authors, however, found nocontamination at other more posterior recording locations and therefore concluded that oEMGdoes not pose a significant problem for closely spaced bipolar sEEG recordings of the typeexamined, except in a very limited region near the temporal pole. Their finding leaves openthe possibility that other recording methods and referencing schemes might be more severelyaffected. In particular, their study did not address how the signal might manifest in recordingsreferenced to a common intracranial or extracranial contact or to a global average, as isfrequently used in human electrocorticography (ECoG). Two other studies have identifiedmore widely distributed muscle artifacts in common-reference ECoG, including low frequencycontamination related to blinks (Ball et al., 2009), and high frequency contamination arisingfrom facial muscle EMG activity during seizures and mastication (Otsubo et al., 2008). Thesestudies establish that eye-movement and motor contamination can affect ECoG under somecircumstances, and that the presence of muscle artifacts in intracranial recordings cannot bediscounted. The recognized potential for saccade-related oEMG to produce misleading resultsin scalp EEG makes the thorough investigation of the presence and distribution of oEMG inintracranial recordings especially important, as well as the identification of measures forsuppressing or ruling out contamination.

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Here we addressed this open issue, using data from epilepsy patients implanted with high-density cortical surface and depth electrodes. We provide a detailed map of the presence anddistribution of saccade related oEMG signals near ventral and lateral temporal cortex. We foundthat under some circumstances intracranial recordings can be greatly affected by eye movementcontamination even at substantial distance from the temporal pole. In particular, we found thatthe intracranial manifestation of the saccadic spike occurs at a similar scale and magnitude asat the scalp. In the present case, we observed that the signal is greatest near temporal pole, inthe vicinity of the affected region described by Jerbi and colleagues, but that in common-reference data it is also detected many centimeters from the poles, affecting in particularrecordings from anterior ventral and medial temporal lobe. In power spectral averages thesignal may resemble visually induced cortical gamma-band responses in both time course andspectral distribution. We observe the effect of the signal in both power spectral measurementsand in interchannel coherence. We consider the importance of reference location in theseobservations. Finally, we evaluated the effectiveness of two forms of spatial filtering,independent component analysis (ICA) filtering and nearest-neighbor bipolar rereferencing.Bipolar rereferencing is often easy to implement offline and is supported by the finding of Jerbiet al, while the application of ICA in the removal of muscle artifact in scalp based recordingshas shown recent promise (Keren et al., 2010; McMenamin et al., 2010). We found that bothmethods reduced the extent of contamination, with ICA performing somewhat more favorablythan bipolar rereferencing alone. Applying these methodological considerations allowed us toclearly separate genuine cortical activity in the gamma range from the eye movement-relatedartifact, and to demonstrate similarities and differences in their time course and spectralcharacteristics. Based on these observations we formulate a set of recommendations on howto avoid mistaking oEMG for cortical gamma band activity in intracranial recordings.

Materials and MethodsSubjects and Recording

Intracranial recordings were obtained from surgically implanted electrodes in 6 epilepsypatients (2 women; mean age 32, range 21–38) during chronic monitoring for corticalepileptogenesis (Howard et al., 2000; Tsuchiya et al., 2008). One subject was excluded fromsubsequent analysis after it was learned that he was amblyopic and therefore did not exhibitnormal eye movements in both eyes. All subjects provided informed consent for theirparticipation in research, and procedures were approved by the University of Iowa Hospitalsand Clinics Internal Review Board.

We recorded simultaneously 128 channels from subdurally implanted ECoG grids, stripelectrodes and multicontact penetrating depth electrodes (Howard et al., 1996) (Ad-TechMedical Instrument Corporation, WI, USA). Grids (8×8 or 8×12) covered the lateral temporalsurface, while 4-contact strip and 16-contact (8×2) grid electrodes were inserted below theventral temporal surface. Depth electrodes were targeted to left and right amygdalae, and leftor right Heschl’s gyrus, and data were obtained from 4 contacts. Subdural strip and grid contactswere 4 mm platinum-iridium discs embedded in a plastic matrix, with 2.3 mm exposeddiameter. Depth electrodes were platinum-iridium cylinders, 2mm in length surrounding aflexible tecoflex-polyurethane shaft, 1.25 mm in diameter. Electrode impedance rangedbetween 5 k–20 k Ohm. Inter-electrode distance was 5 mm for grids and 10 mm for strip anddepth contacts. In each case data were recorded referenced to an extracranial channel implantedunder the galea near the cranial vertex. Data were recorded continuously at a sampling rate of24.4 KHz, filtered from 1.6 Hz to 1000 Hz and decimated to 2034.5 Hz before storage. Allacquisition and online processing was carried out by dedicated research equipment (RX5 andMedusa Preamp, Tucker Davis Technologies, Alachua, FL), which recorded in parallel with



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clinical recording equipment. Data acquired continuously during experimental blocks werestored to hard disk for later processing.

Stimulus PresentationStimuli were presented on a 17 inch LCD monitor (ViewSonic VX922, ViewSonic Corp.,Walnut, CA) at 1024 × 768 resolution and a distance between 63 and 76 cm. Stimuli weregenerated on a Dell Optiplex GX280 PC computer (Dell Inc., Austin, Texas) using the softwarePresentation (Neurobehavioral Systems, Albany, CA). Event signals generated by the parallelport of the stimulus presenting PC indicated trial onsets and button presses and were recordedas analog inputs to the eye tracking system and digital inputs in the signal acquisition system.Event signals were used for offline alignment of eye movement and electrophysiological dataafter accounting for a 25 msec (3 video frames) processing lag in the output of the eyetrackerand a measured 23 msec (± 0.4 msec) lag between the event signal and the first video framecontaining the stimulus.

TaskAll patients engaged in a task requiring overt visual search for upright and inverted faces(Figure 1). The task was divided into blocks of 72 trials. In each trial a fixation cross appearedfor a random duration between 1 and 2 seconds. Following the offset of the fixation cross, afield appeared containing three upright and three inverted faces pseudorandomly positionedon a noisy background. Faces in the search array consisted of randomized genders (three malesand three female) and emotional expressions (two happy, two fearful and two neutral). Eachpseudorandom stimulus was presented no more than once, none were shared across blocks,and all patients viewed the same sequence of stimuli in a given block, while block order wasrandomized across subjects. Subject 1 completed four blocks and all others completed 2. Facessubtended approximately 2 deg. horizontal and 4 deg. vertical arc and were randomlypositioned on a field approximately 26 by 20 deg. The minimum center-to-center distancebetween faces was about 4 deg. Subjects were instructed to remember either upright or invertedfaces, according to block. After four seconds, the search stimulus was removed and then aprobe face was presented following a randomized approximately Gaussian delay with mean0.5 s and s.d. 0.05 s. The probe face remained visible for a random Gaussian interval of 1s withs.d. 0.1. Using a button press, subjects indicated whether the probe face matched any of thetarget faces from the previous search array in both identity and facial expression.

EyetrackingEye movements were monitored with a remotely mounted infrared video eye tracking system(ASL 6000, Applied Science Laboratory, Bedford, Mass.), which sampled gaze position at119.65 Hz. Effective resolution of gaze position was typically between one and two degree ofvisual arc.

The electrooculogram (EOG) signal was also collected in one subject (patient 149) using a 4-channel montage referenced to the mid forehead. Two electrodes were placed near the outercanthi of the left and right eyes and two above and below the right orbit. The signal was firstbandpass-filtered from 1.6 Hz to 1000 Hz and then decimated to 2034.5 Hz before offlinestorage.

We identified saccade onsets using a velocity threshold algorithm described by Engbert andKliegl (Engbert and Kliegl, 2002) and implemented in Matlab scripts made available by theseauthors for download at http://www.agnld.uni-potsdam.de/~ralf/MS/. Briefly, eye velocity wasestimated over a moving average of five samples. Periods when estimated velocity exceeded6 standard deviations for at least 3 samples (25 msec) were identified as saccades. Saccadeonset, duration, direction and amplitude were computed from extracted saccades.



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http://www.agnld.uni-potsdam.de/~ralf/MS/

Analysis of iSSPWe computed the mean amplitude and waveform of the intracranial saccadic spike potential(iSSP) in two ways. In the first analysis we computed the average time-locked to unalteredsaccade onsets as extracted from the eye-movement data. We developed the second analysisin order to address the problem of systematic bias in the estimate of mean iSSP amplitude andwaveform, which arises from timing error in saccade extraction. Inevitably, some error isintroduced from noise in the gaze position signal and by the sampling period of the eye tracker,which at 8.3 ms falls below the Nyquist frequency for most of the spectral range of the iSSP.Both factors are expected to contribute to significant variability in the alignment of phase ofthe iSSP across fixations. As a consequence of such timing error, average iSSP amplitudewould be underestimated, and the contribution of high frequencies attenuated, especially abovethe Nyquist frequency of the gaze position sampling. We therefore improve the timing ofsaccade onset extraction on the basis of the oEMG contamination, itself, which has greatertemporal precision than the gaze record, and adequate signal to noise ratio in selected channelsto be detected in the raw data (e.g. Fig. 2A). This “corrected” saccade onset time was computedfrom peaks in the 20–200 Hz power within the channel with the greatest average saccade-onsetassociated band-power increase. Selected channels are listed in Table 1. In the first step thedata were bandpass filtered between 20 and 200 Hz, and the complex analytic signal wasobtained from the Hilbert transform. The complex modulus of the Hilbert transformed signalgives the instantaneous amplitude envelope. For each subject the channel with the largest meanperisaccadic increase in log envelope was selected for further processing, and the correctedonset times extracted from this channel were used in the alignment of all others. Within a 200ms window centered on each saccade onset extracted from eye-tracking data, the 20–200 Hzband envelope from the selected channel was weighted by a Hanning window and the maximumof the weighted signal within the window became the point of alignment in subsequentaveraging. The resulting shift in the onset time fell within a narrow peak (95% interval ofapproximately 50 ms width) offset by between −40 to +10 ms across subjects with respect tothe originally extracted saccade onset time (Supplemental Figure 1). Note that this proceduredoes not introduce systematic bias in the estimate of iSSP peak-to-trough amplitude becausethe correction was made with respect to the signal envelope, whereas iSSP amplitude wasestimated from the average of the raw signal. The envelope-shifted average therefore reflectsthe systematic relationship between phase and power envelope. For a signal with a randomphase-envelope relationship, the procedure is expected to increase the variance of the estimatebut not to result in a systematic positive or negative bias. This procedure was only applied inestimating the mean iSSP waveform and peak-to-trough amplitude, and not to estimates ofperi-saccadic spectral and band-power perturbation described in following sections, as theprocedure is expected to introduce systematic bias in the average of signal power.

In computing both corrected and uncorrected averages, only saccades which fell within the 4-second duration of a trial were included in the analysis, and all available blocks were includedfor each subject. The number of included trials was 288 for subject 1 and 144 for all others,and the number of saccades onsets was 3318, 1402, 1372, 1571, and 1327, respectively. Peak-to-trough amplitude averages were computed as the average voltage difference between fixedpeak times, with respect to corrected saccade onsets. For each subject, peak times wereextracted from the channel with maximal saccade onset band power perturbation. Peak timeswere not observed to vary substantially between channels (although in a few cases polarityreversed), and peak-to-trough amplitude was computed for all channels at the same extractedpeak times. Statistical analyses of amplitude were carried out by applying a two tailed t-test(H0: μ= 0). To correct for multiple comparisons, we applied false discovery rate (FDR) criteriato P-values across all channels (Benjamini and Hochberg, 1995; Benjamini and Yekutieli,2001). We considered a channel to have a significant iSSP response if the p-value corresponded



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to a false discovery rate q value, less than or equal to 0.01, where q is the expected proportionof falsely rejected null hypotheses across all significant tests.

Comparison of the envelope-shifted iSSP (averaged with respect to corrected saccade onsets)and the unshifted iSSP (using uncorrected saccade onsets) revealed that the unshifted iSSP hada comparatively smaller peak-to-trough amplitude (median ratio 0.52 for all channels in whichiSSP exceeded 10 μV) and attenuation at higher frequency, both of which are expected fromrandom timing error. We also observed decreased variance of peak-to-trough amplitudes aftershifting (median decrease of standard deviation, 4.83, 4.62, 0.41, 4.75, 3.38 μV for each subject,respectively, across all channels in which iSSP amplitude exceeded 10 μV), consistent with areduction of inter-trial alignment error. We note that this procedure is useful for obtaining amore temporally precise estimate of eye movement onset based on the combination of eye-tracking and oEMG signal because the saccadic spike bears a close and consistent relationshipwith the onset of eye movement (Keren et al., 2010). All data on the iSSP peak-to-troughamplitude, as well as mean waveform use the corrected saccade-onset times, whereas all dataon perisaccadic band-power and spectral perturbation use the uncorrected saccade-onset times.

To evaluate the dependence of iSSP amplitude on saccade amplitude and direction, weexamined the iSSP in the EEG channel with the largest amplitude iSSP in each subject,normalized by the mean iSSP amplitude for saccades greater than 10 degrees, and pooled acrosssubjects. In the pooled data, we fit an eighth-order polynomial to estimate mean peak-to-troughamplitudes as a function of saccade amplitude (Figure 5). Separate polynomial fits were alsoobtained for ipsi- and contraversive saccades. In each case all saccades were consideredipsiversive if the x-component of the difference of gaze position before and after the saccadewas negative (positive) for left sided (right sided) contacts, and contraversive otherwise.Polynomial order of 8 was chosen as it minimized bias corrected Akaike’s information criterion(AICc) (Akaike, 1974;Hurvich et al., 1998).

Independent Component Analysis (ICA) Estimation and FilteringICA refers to a family of algorithms that find a linear projection of a multivariate signal whichmaximizes statistical independence of the elements of the signal under the transformation(Hyvärinen and Oja, 2000). The goal in applying ICA is to find a linear projection which“unmixes” distinct physically meaningful sources that contribute to the original signal. Thealgorithm assumes that sources are mutually independent and that the number of sources doesnot exceed the number of channels. Among other applications, it has shown promise in theisolation and removal of motor artifacts (Jung et al., 2000a; McMenamin et al., 2010) fromEEG, notably the saccadic spike potential (Keren et al., 2010). In order to improve the validityof the constraint on the number of assumed source, we applied a 20 to 200 Hz bandpass filterto the signal, removing the contribution from signals outside the peak frequency range of theiSSP. This bandwith was chosen on the basis of the characteristic spectral range in which thecontribution of the SSP tends to be large relative to background EEG (Keren et al., 2010;Yuval-Greenberg et al., 2008), which we find to hold for the iSSP as well (Fig. 13) We appliedthe Bell-Sejnowski ICA algorithm (Bell and Sejnowski, 1995), implemented in the EEGLabtoolbox for Matlab (Delorme and Makeig, 2004) to each subject’s data concatenated across alltrials (i.e. intertrial periods were excluded).

A critical step in the application of ICA is the identification and interpretation of the resultingcomponents. Identifying components which correspond to motor contamination may rely onproperties of the signal and on the spatial distribution of the signal over receiving contacts,revealed by the coefficients of the mixing matrix (Jung et al., 2000b; Keren et al., 2010;McMenamin et al., 2010). In the present case we selected components based on the increasein 70–100 Hz power within the 100 msec window centered on saccade onset relative to the−150 to −50 msec window preceding onset and secondarily on the distribution of mixing



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weights. Components were identified as containing significant oEMG based on the magnitudeof the response.

To filter the data of the independent components containing the greatest saccade onset-associated power increase, we removed the first 2 sorted independent components. We selected2 as the cutoffs, as removing higher components resulted in a little additional reduction ofperisaccadic power (Figure 8) and because the dependence of iSSP amplitude on saccadedirection, described in the results, implies at least two sources, corresponding to left and rightextraocular muscle groups. Filtering was done by nulling the corresponding rows of the mixingmatrix and projecting back into the space of the original signal, which gives a lineartransformation of the original data:

where Q is the product of the modified mixing matrix, M*, in which the columns correspondingto the discarded independent components are set to zero, and the unmixing matrix: Q =M*M−1.

Wavelet analysisTime-frequency spectral estimates were computed using the complex Morlet (Delprat et al.,1992) wavelet. The time-varying spectral estimate S at time t and frequency f is given by theconvolution

where

Power at each time and frequency point is given by the squared modulus of the complex value,S. The bandwidth parameter, α, was chosen to be 7. Data were normalized at each frequencybin by subtracting the average log power in a preceding reference period. In each case theaverage of the log power was used rather than the log of the average power in order to reducethe effect of the large positive skew in the distribution of power. Results, however, were notfound to depend heavily on the choice of transformation. Data were rescaled into dB bymultiplying with a factor of 10/log(10).

We obtained time-frequency plots of log spectral power averaged around the time of saccadeonset by first computing the wavelet transform for the entire duration of the recording across4 Hz – 200 Hz, and then computing the average of log power within a 1000 ms window centeredaround the saccade onset. Average power was normalized in each frequency band bysubtracting average log power in the −500 to − 200 ms window preceding the saccade onset.Time frequency plots averaged with respect to onsets of the search array (“trial-onset average”)were obtained similarly and normalized by the −400 to −100 ms baseline fixation periodpreceding the trial onset. Only saccades whose onsets fell within the 4-second duration of thesearch stimulus were included in the analysis. For statistical analysis we applied a paired t-teston the difference between log power in the stimulus period and mean spectral power in the



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baseline fixation period at each time point. Statistical tests accounted for multiple comparisonsby applying the false discovery rate adjustment (FDR) (Benjamini and Hochberg, 1995) acrossall time-frequency points and all channels.

Perisaccadic powerIn order to evaluate the effect of saccade onset-related spectral perturbation around theobserved spectral peak for the iSSP, the signal was filtered from 70 Hz to 100 Hz with a highorder FIR bandpass filter, and mean power was computed within a sliding 50 ms window. The70–100 Hz band was chosen because it lay near the middle of the observed iSSP related broad-band spectral response, and because it avoids possible line noise at multiples of 60 Hz. Averagelog power was computed time-locked to saccade onset, detected by the eye tracker (withoutusing envelope alignment, see above) and to trial onset. We evaluated perisaccadic band powerperturbation by normalizing to mean power in a −150 to −50 presaccadic baseline period whichtended to fall within the duration of the preceding fixation (green bar in a top left panel of Fig.13). Trial-onset averages were normalized with respect mean power in the preceding −400 to−100 ms window. For statistical analysis we applied paired t-tests on the difference betweenlog power in the test period and the baseline fixation period. Statistical criteria were adjustedfor multiple comparisons by applying false discovery rate (FDR) criteria across all time pointsand channels. We considered a channel to show significant evidence for spectral perturbationif the minimum p-value corresponded to a FDR q-value of 0.01 or less.

Contribution of the iSSP to spectral and band-power perturbationBecause changes in perisaccadic power may reflect cortical sources as well as iSSP, weevaluated the contribution of iSSP by observing the effect of ICA filtering on the band-passpower between 70 and 100 Hz and in wavelet spectrograms ranging from 4 to 200 Hz. In bothcases the same wavelet and power spectral analyses described previously were carried outbefore and after ICA filtering (Figures 10, 12, 13). Four separate contrasts on log power werecomputed: (1) the increase over baseline before filtering, (2) the increase over baseline afterfiltering, (3) the differences in the increases over respective baselines between filtered andunfiltered data, and (4) on the difference of log power between filtered and unfiltered datawithin the respective epochs without normalization to the respective baseline. In each casestatistical validation was carried out as paired t-tests, with significance criteria set by falsediscovery rate (FDR q = 0.01).

Contrasts 1 & 2 are shown in figures 10, 12, 13. Contrast 3 is performed on the differencespectrograms shown in figures 12 & 13, while contrast 4 is shown for band power within the0–500 ms post trial onset epoch in figure 10D. Contrast 4 gives an estimate of the contributionof the two filtered independent components to overall power. Contrast 3 is less sensitive to thepresence of the signal than 4 because it does not remove residual variability within each epoch.It gives a better measure of the practical consequence of contamination, however, as it reflectsthe change in power arising from the correlation between saccade frequency and stimulus onset.

Multitaper coherenceWe computed interchannel coherence using Thomson’s multitaper spectral estimators(Thomson, 1982) within two 100 ms windows centered at −100 ms and 0 ms relative tounshifted saccade onset. Multitaper spectral estimates were obtained by multiplying the datain the window of observation with two orthogonal tapers from the discrete prolate spheroidalsequence (DPSS), which optimally suppresses spectral leakage outside the window ofresolution, resulting in effective frequency resolution of 15Hz. Total spectral power and cross-spectral power were computed as a weighted sum across the two tapered windows.

Coherence was computed pairwise for all channels using the formula



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where Swti(f) is the multitaper spectral estimate for the wth window, tth taper and ith channel.The factor λt is the eigenvalue associated with the tth taper, and is close to 1 for the DPSS tapersused. The parameter w sums over all saccades included in the analysis.

A bootstrapped distribution for the difference of coherence between the presaccadic windowand the saccade-onset window was obtained by recomputing coherence from the original dataafter randomly resampling with replacement. 250 bootstrapped estimates were computed andstatistical thresholds estimated from the resulting empirical distribution. For the purpose ofdisplay in Figure 15, a change in coherence was considered significant if zero fell outside theP > 0.01 two-tailed confidence interval (that is, if the smallest bootstrap estimate among the200 exceeded zero or the greatest estimate was less than zero) at more than half of the frequencysamples in the 40–100 Hz range. Only values that meet this criterion are plotted.

Image CoregistrationBecause the iSSPs are similar across subjects in terms of amplitude, morphology (Fig 2C), anddistribution, analyses of iSSP distribution were carried out on average waveforms pooledacross subjects. For each subject, electrode locations for subtemporal and depth electrodeswere manually identified in a CT volume coregistered to a T1 structural MR scan. All individualT1 images were coregistered with the MNI152 whole head template image (Evans et al.,1993) using a seven-parameter linear transformation which permitted rotation, translation andglobal rescaling. The parameters were estimated using an unsupervised nonlinear optimizationmethod implemented in the FSL toolbox (Jenkinson and Smith, 2001;Smith et al., 2004), withnormalized correlation as the cost function. We used the seven-parameter linear transformationin order to preserve spatial isotropy.

Cortical surface renderings were generated from the T1 image of patient 4. In order to projectcontact locations on the rendered image, locations for all subjects were transformed from thereference space into the image space for patient 4 using the inverse of 4’s transformationobtained in the previous step. The co-registered locations were visually inspected in both thereference volume and the surface rendering to verify accurate correspondence between theoriginal location and the transformed location.

Because CT imaging artifact made the identification of individual contact locations difficultin the densely spaced lateral grids, we applied a different procedure in the coregistration oflateral grid contacts. Contact locations for the lateral grids were determined from intraoperativedigital photographs on the basis of sulcal and gyral landmarks. These were projected onto 2Drenderings of the lateral view of the cortex. For each subject the lateral 2D rendering wasregistered to that of patient 4 using a linear transformation which minimized squared distancebetween a set of manually selected fiducial points.

For all contacts in which iSSP exceeded 10 μV (which did not include any of the lateral gridcontacts), MNI coordinates are reported in Supplemental Table 1. Reported structural labelsare obtained through FSL from the Harvard-Oxford probabilistic atlas (Caviness et al., 1996).In each case the reported structure has maximum probability at the reported MNI coordinate.



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Non-specific artifact identificationWe identified trials which contained possible artifacts, nonspecific to eye movement, using athreshold criterion on the raw signal. Samples which deviated more than 5 s.d. from the meanwere flagged as outliers. Rejecting trials within each channel which contained any outliers of5 s.d. or more over the course of the trial resulted in a median rejection rate across channels of2.4%, 4.2%, 9.7%, 5.2%, 4.2% trials respectively for subjects 1 to 5, with 2.5% to 97.5% inter-quantile intervals of (0.3%, 10.1%), (0%, 24.3%), (2.1%, 22.3%), (0 %, 24.3%), (0%, 13.2%),respectively. In most cases outliers were caused by interictal discharges, and channels in whichrejection rate was high showed frequent interictal activity. Because interictal discharges didnot interfere with the observation of the iSSP, and because discarding trials did not appreciablychange the results, we included all trials and channels in the presented analysis.

ResultsThe intracranial saccadic spike (iSSP)

In all five patients, the onsets of saccades were associated with a biphasic potential, theintracranial saccadic spike (iSSP)(Figure 2), which closely resembled the scalp saccadic spikein waveform and time course (Becker et al., 1972). The response was observed both in subduralECoG (Figure 3) recordings and in depth recordings from anterior temporal lobe and Heschl’sgyrus (Figure 4). Peak-to-trough amplitude differed significantly from zero at a majority ofcontacts in most subjects over all observed regions. The numbers of contacts in whichamplitude reached significance were 124, 88, 52, 120 and 123 respectively for subjects 1 to 5,out of 128 channels in each subject. Amplitude was greatest near the temporal pole andremained substantial mesially and anterior to the brainstem, with a magnitude greater than 10μV over roughly the anterior half of the ventral temporal surface. Locations and amplitudesfor the channels with the largest iSSP in each subject are listed in Table 1, and all channelswith amplitude greater than 10 μV are listed in Supplemental Table S1. The response alsoshowed a large medial to lateral gradient, diminishing at more lateral contacts and in a fewcases reversing polarity at anterior ventrolateral contacts. This pattern is particularly apparentin depth electrodes and in ventral ECoG grids. In depth contacts targeted to anterior medialtemporal lobe, iSSP amplitude decays sharply with increasing laterality (Fig. 4). In all subjects,the reference electrode was located outside the skull, embedded below the galeal membranenear the vertex. Thus, the possible contribution of the reference electrode to contamination isan important issue, which we will consider in further detail.

Effect of saccade amplitudeThe visual search task encourages subjects to generate frequent large amplitude saccades,which may tend to exaggerate the severity of any eye movement related contamination. Wetherefore examined the dependence of oEMG contamination on saccade amplitude. Thedistribution of saccade amplitudes was bimodal (Figure 5), reflecting a subset of saccadeswhich remained within faces another which switched between faces. The former fell below 4degrees amplitude and the latter were typically greater than 4 degrees, reflecting the minimumdistance between faces. Because subjects generated a wide range of saccade amplitudes overthe course of the task, the data allow an examination of the dependence between saccadeamplitude and oEMG contamination. We observed that iSSP amplitude depended on saccadeamplitude in a nonlinear fashion, with a rapid increase for saccades of less than 8 degrees,approaching a stable plateau beyond 8 degrees (Figure 5). For saccades of 2 degrees, the meaniSSP amplitude averaged across all subjects was 33% of the value at the plateau, taken as themean for saccades above 10 deg, and 43% of the mean across all saccades. The significanceof the nonlinearity was confirmed by a sequential likelihood ratio test on the polynomial terms,for which each additional term reached a significance threshold of P < 0.01 up to the fourthorder term. The data were fitted with an 8th order polynomial, as this order minimized Akaike’s



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information criterion (AIC). The iSSP amplitude also showed significant dependence onsaccade direction: at the temporal pole, ipsiversive saccades were associated with larger iSSPsthan contraversive (Fig. 5). These observations agree with the amplitude and directiondependence reported for the scalp SSP (Boylan and Doig, 1989;Riemslag et al.,1988;Thickbroom and Mastaglia, 1986).

The nonlinearity of the response suggests that the practice of discarding intervals which containsaccades above some amplitude threshold may not reliably eliminate contamination. Inparticular, thresholds based on the EOG signal may be insensitive to small amplitude saccades,as eye-movement related deflections in EOG scale linearly with saccade amplitude (Yuval-Greenberg et al., 2008). We therefore examined the dependence of mean iSSP amplitude acrossall channels for saccades which fell in amplitude intervals of 0° to 2° (median N = 270), 2° to4° (med. N = 163), 4° to 6° (med. N = 194), 6° to 8° (med. N = 220), and 8° to 10° (med. N =225). For all subjects iSSP amplitude and the proportion of channels in which significant peak-to-trough amplitude was observed increased with saccade amplitude up to 6° to 8° and leveledoff in the 8° to 10° range, agreeing with the aforementioned nonlinearity. In all subjects a largefraction of channels showed significant iSSPs at all saccade amplitude intervals greater than 4deg (Figure 7). A significant response also remained in a subset of channels for saccades ofless than 2° (median 8 of 128, range 2 to 20) over the anterior third of the ventral temporalsurface (Figure 6). For saccades of 2° –4° the median number of significant channels was 28with a range of 15 to 41. For the remaining amplitude intervals the medians were 42, 46 and51. Small amplitude saccades of less than 2° therefore generated a detectable iSSP with a morerestricted distribution than larger amplitude saccades.

ICA filteringIn order to better characterize the contribution of the oEMG signal to the observed responsesand to explore methods for removing the contaminant, we applied independent componentspatial filtering (ICA) to the signal. ICA has shown promise in reducing contamination fromoEMG and other myogenic sources (Keren et al., 2010; McMenamin et al., 2010) in scalp EEGrecordings. In all subjects sorting of independent components returned a single componentwith a large iSSP waveform and one or two other components in which residual oEMG wasdiscernible in the band-pass filtered mean perisaccadic power (Figure 8). In each case thedistribution of mixing weights of the first sorted component closely resembled the distributionof iSSP peak-to-trough amplitudes, and spikes were readily observed in the band-pass filteredunaveraged data (Figure 8b). To suppress oEMG contamination we removed the first two sortedcomponents, as removing further components provided little apparent improvement, andbecause at least two source are required to explain the dependence between horizontal saccadedirection and iSSP amplitude. To evaluate the effectiveness of this procedure we comparediSSP amplitude (Figure 9) and perisaccadic wavelet power (Figure 13) before and afterfiltering, as well as the effect of filtering on spectral perturbation time-locked to trial onset(Figure 10 and 12), and interchannel coherence (Figure 15). Residual iSSP amplitude andchange in perisaccadic power at contacts near the temporal pole, visible in figures 6 and 7,most likely reflects residual oEMG contamination affecting mainly channels nearest theoculomotor sources.

Bipolar rereferencingWe examined the effectiveness of bipolar rereferencing (BPR) in suppressing contamination.BPR is a simple form of spatial filtering that applies a difference between selected pairs ofneighboring channels. Like ICA filtering, BPR reduced the extent of the iSSP beyond thetemporal pole, as measured by iSSP amplitude (Figure 9) and coherence (Figure 15). Theamplitude of the iSSP was diminished, but it remained observable in many of the channels nearthe anterior half of ventral temporal cortex. Combined ICA and bipolar rereferencing resulted



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in the most effective suppression of iSSP amplitude, however in all cases residualcontamination remained near the temporal poles.

Saccade-related band power and spectral perturbationIn channels near the temporal poles and in all patients, wavelet time-frequency analysisrevealed a broad increase in power above 20 Hz, within the 100 msec window around saccadeonset (Figure 13). This response is attenuated further from the pole and absent at posteriorcontacts. Representative examples of wavelet spectrograms are shown at the respectivelocations: contact TP near temporal pole, MVTM near the mesial section of middle ventraltemporal cortex, and PVT over posterior ventral temporal cortex. In the period −150 to −50msec before saccade onset, which typically fell within a period of stable fixation (Figure 13),contacts TP and MVTM showed a decrease of power in the same frequency band with respectto the baseline period (left upper and middle panels in Figure 13). In both the trial onset average(Figure 12) and the saccade onset average (Figure 13), responses in TP and to a lesser extentMVTM closely tracked the histogram of saccade onsets, a consequence of the saccade onsetassociated spectral perturbation. Across trials, the first saccade following the stimulus onsetfell within a characteristic interval of between 200 and 300 msec, leading to a peak in both thehistogram of saccade onset times and the wavelet spectrogram at contact TP and to a lesserextent at MVTM. A second smaller peak appears between 400 and 600 msec after thetermination of the first fixation. The initial peaks are followed by a prolonged elevation ingamma power over the remaining duration of the trial.

Although saccade onset-related changes are easy to show in the saccade-triggered averages, akey question is whether and to what extent increases in stimulus-onset triggered averages canbe attributed to eye muscle contamination. In general the answer is expected to depend on thetask and the number of repetitions, as well as the presence and magnitude of any corticalresponses, in addition to the magnitude of oEMG contamination. All of these may affect thecorrelation between oEMG power and factors of interest in the experimental design. For thecurrent visual search task, numerous channels show significant (FDR q-value = 0.01)modulation of the power in the gamma range following stimulus onset (Figure 10) in thepositive direction (56, 26, 57, 52 and 36 contacts out of 128 respectively for subjects 1 to 5),and in each case a smaller number showed significant reduction of gamma power (11, 19, 2,10 and 3 contacts, respectively). Channels in which there is a large iSSP show a saccade onset-following response in the trial average, which is suppressed by ICA filtering (Figure 10 and12), establishing that the response in the trial average is related to eye movement contamination.In the posterior contact PVT, a large response at the trial onset is not associated with any saccadeonset response (Row 3, Figure 13), and is not affected by ICA filtering. Thus the response inPVT cannot be attributed to oEMG contamination. Interestingly, PVT does show a post-saccadic modulation characterized by suppression of the gamma response followed byenhancement, a pattern which resembles saccade related modulation of multiunit activity(Rajkai et al., 2007; Ringo et al., 1994).

To show the contribution of contamination across all channels, the 70–100 Hz band was chosenfor further analysis as a representative bandwidth within the range of observed broad-bandgamma modulation, which avoided 60 and 120 Hz bands likely to be affected by line noise.Mean 70–100 Hz log power was computed within the window 0 – 500 msec following trialonset. Significant elevation of power above the baseline is suppressed by ICA filtering withinthis window in channels clustered over the anterior half of the ventral temporal surface (Figure10C). The contribution of the filtered components to power within the window is large (~ 1dB) over the anterior third and declines rapidly to less than 0.5 dB within the middle third(Figure 10D). Over the posterior third the effect is negligible. In total, channels which showeda significant increase in gamma power before ICA filtering but not afterward numbered 8, 9,



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22, 15 and 14 out of 128, respectively, for the five subjects. A total of 4 channels, 3 for subject2 and 1 for subject 1, showed a significant response after filtering, but not before. Channels inwhich the response was significant both before and after filtering numbered 67, 28, 37, 47, and25, respectively.

Comparison of oEMG and visual responseAs noted, numerous contacts showed increases in gamma-band power which was not attributedto eye muscle contamination. The comparison of responses in PVT and the contaminated signalin TP (Figure 14A) reveals a surprising similarity in the time-course and the magnitude of thetwo responses, especially with respect to the onset peak. Figure 10B shows the data from TPand PVT sorted with respect to the delay between trial onset and the first saccade, revealingagain that the response in TP is strongly time-locked to the occurrence of saccades. Theresponse in PVT, in contrast, shows no sensitivity to the timing of saccades. Although the tworesponses are otherwise easily distinguished from each other on the basis of anatomicalseparation, they cannot be reliably distinguished from each other on the basis of time coursein the trial average. As seen in figure 12 the responses also share a similar bandwidth, thusspectral features and time-course of the responses provide no obvious gross attributes by whichto distinguish oEMG contamination from neuronal signal. Some subtler differences areapparent, however: in the case of oEMG in TP contamination the initial peak is followed by atrough, which reflects a decrease in saccade frequency following the initial peak, related to theduration of the succeeding fixation. This trough is not present in the visual response in PVT.The spectrum of oEMG contamination also extends into a lower frequency range, toapproximately 20 Hz, whereas the response in PVT is confined to frequencies above 40 Hzand is accompanied by suppression of lower frequencies. These differences might be used todistinguish oEMG contamination from cortical gamma-band responses in some cases, althoughwe cannot establish how reliably these features accompany the respective signals. Thepossibility that the observed response may be a mixture of oEMG and cortical sources is likelyto further limit their usefulness.

CoherenceMeasures based on cross-spectral power, such as coherence, may be especially susceptible tothe effects of contamination when compared locations are affected by volume conduction froma common source. We therefore examined saccade-onset-related changes in interchannelcoherence (Figure 15). The change in the distribution of coherence between the presaccadicand saccade-onset windows at each frequency pooled across all channels and subjects providesa global summary of the frequency ranges most affected by contamination. In Fig. 15E adifference is visually apparent between 40 and 110 Hz, and is confirmed by the one-tailed rank-sum test on the equality of medians, indicating that median coherence in the aggregate data isgreater in the saccade onset window than in the reference window with P < 0.001 within eachfrequency band from 40 to 110 Hz.

A subsequent analysis examined pair-wise coherence changes within the 70 Hz to 100 Hzrange. As shown in Figure 15A, a significant increase in coherence is centered on anteriorchannels near temporal pole but also extends widely over much of anterior and lateral cortex.In channels over posterior and lateral temporal cortex, significant changes in coherence involveventral anterior and medial channels where the iSSP is greatest.

Threshold-based artifact rejectionIn EEG recordings eye-movements often appear as large amplitude voltage fluctuations, whichreflect contamination by the EOG signal. Such large amplitude fluctuations may be detectedand discarded using simple threshold-based artifact rejection. We therefore examined theusefulness of a threshold-based procedure in detecting and removing eye movement related



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contamination. We compared the number of peri-saccade onset windows (−50 to 50 ms withrespect to saccade onset) which contained voltages that exceeded threshold with the numberof presaccadic baseline windows (−150 to −50 ms) across all saccades, during which therewere few saccades. Using a 5 s.d. criterion, a difference between the windows was observedat an uncorrected p-value of .05 in 13 channels across all subjects, of which only 1 channelremained significant at q = .05 after applying FDR correction. This channel was a temporalpole contact for which iSSP peak-to-trough amplitude was 45.6 μV. At a lower thresholdcriterion of 4 s.d. the number of contacts showing a significant difference increased to 4. Thuseye-movement related artifacts either from muscle, EOG, or other sources did not create a largeamplitude disturbance that could be reliably detected using a simple threshold, except in a smallnumber of highly affected channels. In general, we did not observe that eye movements wereassociated with obvious large amplitude fluctuations in the unfiltered data, such as might arisefrom EOG contamination Thus we conclude that simple threshold-based artifact rejection isnot effective for removing oEMG contamination.

DiscussionWe have shown that ocular-muscle electromyogram (oEMG) contamination of intracranialrecordings, particularly in the form of the iSSP, is observable throughout much of the recordedarea and that contamination may affect power-spectral measurements. The iSSP closelyresembles the saccadic spike as described in scalp recordings with respect to waveform and inits dependence on saccade amplitude and direction (Becker et al., 1972). The spatial gradientof iSSP amplitude apparent in Figure 3 and 4 suggests a source near and slightly beyond thetemporal pole. On depolarization, the extraocular muscles generate a dipole moment that isgrossly aligned with the extraocular muscles (Thickbroom and Mastaglia, 1985; Yuval-Greenberg et al., 2008). As anterior medial contacts lie nearer to the expected axis of this dipole,the medial to lateral gradient apparent in figures 3 and 4 provides further evidence for an ocular-muscle source. We therefore conclude that the scalp and intracranial saccadic spike arise froma common source.

While the iSSP can be detected over a broad area covering most recorded locations, the spatialdistribution of the effect on trial-onset averages of power in the gamma range is more restricted(Figure 10), affecting mainly locations in the anterior half of temporal cortex. Large visualresponses following the onset of the trial were most apparent over the posterior half, and thusdid not substantially overlap with the regions most affected by contamination. Within themiddle section of ventral temporal cortex (e.g. contact MVTL, Fig. 10E), small amplitudevisual responses appeared to overlap with oEMG contamination, leading to potential ambiguityin the source of the more subtle response.

We also observed that spectral characteristics and time course of eye movement contaminationin contacts near temporal pole can closely resemble gamma-band visual responses recordedelsewhere in the same patients. This emphasizes the potentially seriously confounding natureof the oEMG contamination: not only can it obscure cortical activity, but it can be mistakenfor it. In the present task, many contacts over posterior ventral cortex, notably near areasresponsive to faces (Allison et al., 1999; Tsuchiya et al., 2008) showed large broad-bandincreases of power in the gamma range (exemplified by contact PVT in Figures 10 to 14). Weverified that these responses do not arise from oEMG contamination, and most likely thereforereflect genuine cortical activity. Like the oEMG signal, the cortical response covers much ofthe observed spectral range between 40 Hz and 200 Hz.

The similarity in the time course of visual responses in some channels and the oEMG signaldeserves special attention. For example, the contaminated signal from contact TP and thecortical response in PVT both show a peak between 200 and 300 ms (Figure 14), followed by



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a sustained elevation of gamma power over the remainder of the trial. This similarity mightsuggest that gamma-band activity in extrastriate visual cortex is correlated with the frequencyof eye movements, a finding which has been described in the BOLD response of primary visualcortex (Kimmig et al., 2001), however the onset and initial peak within the high gammaresponse in PVT did not otherwise closely follow the latency to the first saccade (Fig. 14B).Moreover, in two adjacent channels, PVT−1 and PVT+1, the peak latencies were shiftedbackwards and forwards in time, respectively (Fig. 14A). In PVT the initial peak represents anonset response following the appearance of the stimulus; the fact that the onset of the firstsaccade coincided with this peak suggests that it is programmed well before this early visualresponse. Targeting of such rapid initiatial eye movements seems likely to depend rather onvery early visual responses in frontal eye field (Kirchner et al., 2009), than on the output ofmore delayed visual processing in ventral temporal cortex.

A second observation concerns the similarity in the bandwidth of the two responses: in the caseof the saccadic spike, the breadth of the spectral response is the signature of a highly transitory,weakly oscillatory (biphasic) signal. Because of variability in timing, averaging smears thisresponse in the time direction, leading to the appearance of a more sustained activation. Thereare three different mechanisms that might produce a similar signature in spectral averages ofthe cortical signal. First, it is possible that the breadth of cortical responses in the gamma rangereflects weakly oscillatory transients, similar to the oEMG signal, which vary in timing fromone trial to the next. Second they might arise from sustained narrow-band oscillations whosemodal frequency varies from one trial to the next, and third they might represent sustainedweakly oscillatory broadband activity which is similar across trials. Finding the properanalytical techniques to distinguish different types of temporal structure that lead to the sameaverage spectrogram is therefore an important matter, which may prove useful for identifyingoEMG contamination.

Dependence on Saccade AmplitudeThe relationship between saccade amplitude and iSSP peak-to-trough amplitude agrees withthe general relationship described in scalp recordings (Boylan and Doig, 1989): iSSP amplitudeincreases rapidly and approximately linearly with saccade amplitude up to 8 degrees, beyondwhich it approaches a stable plateau (Figs. 5, 6, 7). One consequence of the rapid increase ofthe saccadic spike amplitude in scalp recordings, is that small amplitude saccades may generatenon-negligible contamination (Keren et al., 2010; Yuval-Greenberg et al., 2008). We observediSSPs in a few channels for saccades of less than 2 degrees, which were restricted to the anteriorthird of ventral temporal contacts. Given the precision of gaze position recordings, we cannotaddress the occurrence of intracranial oEMG during microsaccades (with amplitude less than0.5 degrees), which cannot be eliminated with instructed fixation. Suppressing large amplitudeeye movements should reduce the practical consequence of contamination in the trial-onsetaverage, and may eliminate the problem altogether in some cases. However we cannot drawstrong positive or negative conclusions on the possible role of small saccades, as the data mayalso be biased by the presence of false positives in saccade detection, which are most likely tobe classified as small amplitude saccades. Given that the iSSP is nevertheless clearly presentin some channels for saccades of less than 2 deg, we recommend that, at a minimum, recordingand reference electrode locations should be considered when ruling out contamination for smallamplitude saccades. A more thorough evaluation of this point will require higher precisioneyetracking.

Contribution of the reference electrodeAt locations distant from the temporal poles, notably posterior ventral temporal cortex andlateral temporal cortex we found contamination to be negligible in its effect on trial-onsetaveraged gamma power. It is therefore tempting to use proximity to the orbit as an additional



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criterion for ruling contamination in or out. However, it must be remembered that the signalreflects the voltage difference between recording and reference contacts, and that the absenceof a signal implies that the voltage fluctuations are equal at both locations, not that that thesignal is truly absent at either location, compared to a perfectly neutral ground. In particular,whether oEMG contamination might be attributed to the reference contact (“referencecontamination”) depends on the magnitude and polarity of the signal at both the reference andthe recording sites. Because in the present case an extracranial subgaleal electrode near thevertex served as reference, an implication is that iSSP-related oEMG appears over much ofposterior and lateral recording locations with a similar polarity and magnitude as at the scalpvertex. Saccadic spike amplitude at the scalp vertex, referenced to comparatively neutral non-cephalic locations, has been reported with the same polarity that we observe in the intracranialrecordings at an amplitude of approximately 15 μV (Thickbroom and Mastaglia, 1985). Withrespect to a hypothetical, perfectly neutral reference, our findings therefore suggest that thesignal is substantial throughout the head and distributed on a scale similar to that at the scalp.Because the polarity of the iSSP at the scalp reference, relative to ground, is expected to be thesame as what we observed at the large majority of intracranial locations, it is also unlikely thatthe choice of reference substantially increased the observed iSSP: had the reference contactintroduced an upward bias in the magnitude of the observed oEMG contamination in anychannels, it should have been accompanied by a widely distributed polarity reversal of the iSSPwithin all channels for which the reference contamination exceeded recording contactcontamination. Based on the known distribution and amplitude of the scalp SSP and theorientation of equivalent source dipoles (Thickbroom and Mastaglia, 1985; Yuval-Greenberget al., 2008), we expect that a more anterior reference would have resulted in a larger and morewidely dispersed iSSP and greater contamination of spectral power in the gamma range. Theseconclusions must be tempered by the fact that we cannot directly infer the amplitude of theiSSP in the reference contact from the present data, and that the presence of surgical bone andtissue defects may cause scalp topography to deviate from the previously reported distribution.That the extracranial reference in the present case was the major source of contamination canbe ruled out with greater confidence from the fact that the response shows a large gradientacross intracranial locations near anterior temporal pole, and that the effect of contaminationin the trial- and saccade- onset averages became negligible at posterior and lateral locations,where the signal is expected to be smallest. The question of the distribution of the signal mightbe further clarified with a detailed model of head conductivity, but it is safe to conclude thatthe choice of reference in intracranial recordings, as in scalp recordings, will have importantconsequences in the likelihood of observing contamination.

Comparison to previous reportsThe present findings complement recent studies which describe motor and eye-movementcontamination of intracranial recordings. Of particular relevance, Jerbi and coauthors alsoobserved the iSSP at a handful of recording contacts near the apex of the temporal pole (Jerbiet al., 2009a), which did not affect more posterior and anterior recording locations. Theyconclude that oEMG contamination in bipolar stereotactic EEG outside of temporal pole islikely to be negligible. We have described contamination with a considerably widerdistribution, affecting both subdural ECoG and depth recordings. This difference can beaccounted for by the methods of referencing used by the respective studies. Jerbi and colleaguesobtained recordings with a nearest-neighbor bipolar derivation spaced at 3 mm. Consistentwith their observation, we found that offline bipolar referencing greatly suppresses the extentof contamination, though not to same the degree described by them. The spacing of bipolarpairs (3 mm) in their report was smaller than what we were able to reproduce in our analysis,as minimum inter-electrode distance varied between 1 cm and 5 mm in our recording arrays.The apparently lower effectiveness of bipolar rereferencing in the present case is likely to bea consequence of greater distance between reference and recording locations. Jerbi and



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colleagues also obtained recordings in the context of a reading task, which may have tendedto favor smaller amplitude saccades than our visual search task. Finally, electrodes wereimplanted in the left hemisphere, while the data were collected in a reading task in which itcan be assumed the large majority of saccades are rightward (contraversive with respect toelectrode location), suggesting that a smaller signal was observed than if leftward (i.e.,ipsiversive) and rightward saccades had been equally frequent (see Figure 5). Our findingscomplement theirs in identifying the appearance of the oEMG contamination in intracranialrecordings, while warranting a greater degree of caution when considering oEMGcontamination in common-reference recordings as well as when using more widely spacedbipolar pairs. Taken together, the studies emphasize the usefulness of local referencing, and inparticular, closely spaced bipolar montages as used by Jerbi and colleagues.

Ball and colleagues compared the manifestation of eye-movement contamination insimultaneously recorded ECoG and extracranial EEG (Ball et al., 2009). They observed blinkartifacts in ECoG recordings from prefrontal cortex, as well as smaller saccade-related artifacts.In both cases the signals resembled blink and eye-movement related components of theclassical EOG signal, which arise from the corneoretinal potential and from blink-relatedchanges in conductivity of the eye, rather than muscle depolarization (Arden et al., 1962; Kris,1958; Miles, 1939). Because saccades were determined from the EOG signal, rather than directrecordings of eye movement, it is likely that alignment error would have suppressed the iSSPin the averaged signal, had it been present, thus the study does not address motor contaminationof the type considered here. Ball et al. also did not report saccade related spectral perturbation,however it is noteworthy in our data that perturbation in the dominant frequency ranges of theclassical EOG signal (below 20 Hz) was absent (Fig. 13). This observation suggests thatoEMG-related gamma-band contamination is substantially larger within the respectivefrequency range, relative to the physiological background, than the contribution of componentsof the classical EOG identified by Ball et al. Thus the current findings suggest importantdifferences between the manifestation of oEMG and EOG contamination and, in particular,that the appearance of one may not be a reliable predictor of the other. This observation suggeststhat methods optimized to remove EOG contamination may not reliably remove oEMGcontamination, and vice versa.

The manifestation of EMG in intracranial recordings has recently been addressed in a casereport by Otsubo and colleagues (Otsubo et al., 2008), who observed widely distributed EMGsignals during chewing and seizure related facial grimacing in a single patient. Of a series of38 pediatric epilepsy patients, the reported case was the only one in which such EMGcontamination was noted. Facial muscle EMG contamination therefore appears to becomparatively unusual and less consistent across subjects than oEMG contamination, whichwe find to be similar in all five observed subjects with respect to magnitude and distribution.Otsubo et al. suggest that facial muscle EMG contamination is likely to depend on the positionof surgical bone defects relative to the recording array (Zhang et al., 2006), and therefore tovary from case to case. We find the oEMG signal, in contrast, to be consistent in its distributionand magnitude across subjects, suggesting that the normal anatomical relationship between theorbital cavity and the intracranial space, which are connected by the superior orbital fissureand optic canal, explain the current spread from one compartment to the other. Furtherclarification of such questions will require anatomically detailed source modeling.

Effect on interchannel coherenceThe effect of contamination from a distant source is especially important to consider whenmeasuring inter-channel coherence and related measures of coupling derived from crossspectra. We find that iSSP contamination manifested as a broadly distributed pattern ofincreased coherence around the onset of the saccade (Fig. 15), which was mitigated by bipolar



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rereferencing and ICA filtering. This observation raises a concern about the use of coherencein common-reference data. It has been suggested that reference contamination is sufficientlylow to permit meaningful computation of coherence in scalp-referenced intracranial recordings(Zaveri et al., 2000). The present finding suggests that a more serious confounding factor arisesfrom common source contamination related to oEMG, rather than reference contamination.Methods which attempt to eliminate the effect of contamination from common sources byremoving zero-phase-lag coherence (Nolte et al., 2004;Stam et al., 2007) might be applicable,however because contamination in this instance arises from multiple mutually coherent sources(left and right extraocular muscles), rather than a single source, it remains possible that a portionof the change in coherence will appear with a non-zero phase lag. That left and right-sidedcontacts mirrored each other in their dependence on saccade direction implies that they wereaffected, at least in part, by different sources. This important issue requires further scrutiny,but we recommend care in ruling out muscle contamination as a source of inter-channelcoupling, particularly when using a common reference.

Distinguishing oEMG from cortical signals: recommendations for future studiesThe current observations suggest some general guidelines for ruling out eye-movement relatedmotor contamination in intracranial data. When eye-movement data are available, the simplestprocedure is to examine spectral power averaged with respect to saccade onset. In the absenceof a saccade-onset associated spectral perturbation, any stimulus-onset response is not likelyto be explained by oEMG contamination. When eye-movement recordings are not available,several options remain. First, oEMG can be suppressed using spatial filtering such as localrereferencing or ICA. Local rereferencing is generally easiest to implement, and we found thatit reduced the extent of the effect on gamma-band power and interchannel coherence, but leftsignificant contamination over the portion of the recorded area where the gradient of theresponse was steep, roughly the anterior third of temporal cortex. ICA filtering requires theidentification of components containing the muscle artifact; although we selected componentson the basis of perisaccadic power, we might also have identified them from the characteristicanteroposterior gradient in the mixing coefficients (Figure 8) and the broad-band spikes whichwere visible in the raw data, whose occurrence followed the expected time course of eyemovements. Similar criteria have recently been applied successfully to component selectionin scalp EEG (Keren et al., 2010); our results suggest they are also applicable to intracranialdata, provided there is adequate spatial sampling to isolate the artifact. Whereas electrodeplacement in scalp EEG recording is highly standardized, placement of intracranial contactsinevitably varies from one patient to the next; thus, the effectiveness of ICA filtering appliedto intracranial data is less easy to predict in advance. Regression based methods provide yetanother alternative (McMenamin et al., 2009;Nottage, 2010), which we have not evaluatedhere. Although we show that small amplitude saccades generate a measurable iSSP signal atsome locations, the magnitude of the signal varies approximately linearly with saccadeamplitude for saccades of less than 8 degrees, and suppressing large amplitude eye movementsmay therefore help further reduce contamination. All of the methods considered here are mosteffective when at least one recorded channel includes significant oEMG contamination, andfuture studies may benefit from extracranial recordings obtained near the orbits that arededicated to extracting the eye muscle signal. For example, in checking for perisaccadicspectral perturbation, one should have one or more channels in which the oEMG signal ispresent to serve as a positive control, which validates the conclusion that any other channelsare free of contamination. ICA is also likely to isolate the oEMG signal from neural sourcesmore effectively when it is present in some channels with high signal to noise ratio. Especiallywhen recording from medial or anterior temporal lobe, or when using common reference orwidely spaced bipolar recordings, adding periorbital extracranial channels to capture oEMGsignal is advisable. Finally, oEMG contamination varies gradually with distance from thesources, and has little variability with respect to time course from one channel to the next.



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Therefore, a further criterion for ruling out oEMG contamination is local heterogeneity in thegamma-band response. For example, the peak times in the responses displayed in Figure 14Aare dissimilar, supporting the conclusion that they cannot be fully explained by a commoncontaminant.

ConclusionIn summary, we find that saccade-related oEMG contamination can affect intracranial EEGobtained with a common reference in much the same way as it can scalp EEG. The assumptionthat intracranial recordings are more robust to oEMG contamination must therefore bequalified. However, we also note that our findings do not fundamentally overturn thisassumption: in the present case the contaminating signal was in most instances easilydistinguished from cortical activity using relatively simple procedures. Contamination whichsubstantially affected stimulus-onset averages was confined to recording locations nearanterior and anteromedial temporal cortex. Although we find that averaged cortical gamma-band responses in ECoG may at times closely resemble oEMG contamination in spectralfeatures and time-course, the distribution of visual responses and oEMG contamination werelargely non-overlapping. An important qualification of this finding is its likely dependence onreference contact location. Nearest neighbor rereferencing substantially reduces the extent ofcontamination, although its effectiveness depends on the spacing between recording andreference contacts as well as their position and orientation relative to the local gradient inpotential. In short, deciding whether oEMG contamination might affect any result requires careand judgment in evaluating all of the parameters of the recording arrangement with particularattention to reference location. Independent component offers a principled way to isolate andremove the contaminating signal in many cases, however its effectiveness is likely to dependon the number and placement of electrodes. Finally, we confirm that broad-band gamma signalsobserved in extrastriate visual cortex are genuinely cortical, and cannot be explained as eye-movement related contamination.

Supplementary MaterialRefer to Web version on PubMed Central for supplementary material.

AcknowledgmentsOlivier David, David Rudrauf, Rick Jenison, Two anonymous reviewers

supported by: NIH Grant R03 MH070497-01A2, NIH Grant R01 D, and Japan Society for the Promotion of Science

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Figure 1.Sequence of events in a trial. A fixation cross is presented for 1 to 2 seconds, followed by asearch array of pseudorandomly positioned faces for 4 seconds, followed by a probe face for1 second. Subjects indicate with a button press whether the probe face matched any face in thepreceding array with respect to orientation, identity and facial expression.



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Figure 2.The intracranial Saccadic Spike Potential. A: Saccadic spikes observed in unaveraged 20–200Hz filtered field potential (black line) from a contact near temporal pole. The top two plotsshow horizontal and vertical gaze position. Yellow lines indicate extracted saccade onset times.Note that the second saccade onset most likely represents a false positive. B: Morphology ofthe iSSP averaged with respect to saccade onset in an intracranial channel (blue line) and asobserved in extracranial EOG contact (black line). In both cases data are bandpass filtered from20 to 200 Hz. Average rectified unfiltered EOG (red) shows the time course of the iSSP inrelation to onset of eye movement. C: iSSP morphology in all five subjects observed in thechannel with maximal peak-to-trough iSSP amplitude. In all subjects the maximal iSSPamplitude appeared in channels near the temporal pole



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Figure 3.Manifestation of iSSP in subdural ECoG recordings. Peak-to-trough iSSP amplitude for allsubjects and ECoG recording locations is shown at center. A. Peak-to-trough amplitude ofiSSP for all channels which reached statistical significance at FDR q-value = 0.01. Channelswhich did not reach the significance criterion are unfilled. Six example waveforms aredisplayed for the indicated contacts. Note that the vertical scale for the waveforms fromposterior contacts differs from anterior contacts in order to aid visibility. B. Peak-to-troughamplitude interpolated over all contacts and subjects.



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Figure 4.Manifestation of iSSP in depth recordings from anterior temporal lobe and Heschl’s gyrus. Infour contact depth electrodes targeted to left (all subjects) and right (subjects 3, 4 and 5)amygdala (circles), large amplitude iSSPs are observed at medial contacts. Smaller iSSPsappear at contacts in Heschl’s gyrus (triangles). Left and right columns show mean iSSP foreach contact arranged in left-to-right order under common subgaleal reference (black) and afterbipolar rereferencing between neighboring channels (gray). Contact location is shown in thecentral column, where color indicates subject identity. As in the subdural ECoG electrodes, alarge medio-lateral gradient is apparent in iSSP amplitude. Eye and extraocular muscle (medial,lateral, superior and inferior rectus) position are shown schematically with green ellipses andred lines, respectively. The most medial right-sided contact for subject 5 was broken and is notshown.



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Figure 5.iSSP peak-to-trough amplitude dependence on saccade amplitude and direction. Peak-to-trough amplitudes in unaveraged data, normalized within each subject to the mean iSSPamplitude for all saccades over 10 deg. Data are taken from the channel with the largest iSSP,which was a contact near temporal pole in each subject, normalized and pooled across subjects.Mean iSSP amplitude as a function of saccade amplitude and 2 S.E.M are shown for ipsiversivesaccades (red), contraversive saccades (blue) and all saccades (purple) in data pooled acrosssubjects. Curves are fitted by an eighth order polynomial, with the order chosen to minimizeAIC. iSSP amplitude increases approximately linearly for small amplitude saccades under 5deg, approaching a plateau beyond 6 degrees. In all subjects ipsiversive saccades generated alarger iSSP than contraversive at the selected temporal pole contact. Mean iSSP amplitude overall saccades in each case is shown by the dashed lines of corresponding color. The histogramshows the relative frequency of saccades as a function of eccentricity.



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Figure 6.Dependence of the distribution and peak-to-trough amplitude of saccadic spikes on saccadeamplitude. The color scale shows mean iSSP peak-to-trough amplitude for saccades which fallwithin the given amplitude range. Only channels which reached an FDR corrected significancethreshold q ≤ .01 are filled.



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Figure 7.Dependence of peak-to-trough iSSP amplitude on saccade amplitude across channels. Meanpeak-to-trough amplitude is shown for saccades which fall within the given amplitude range.Responses are colored red if they are significantly different from 0 at FDR correctedsignificance threshold q ≤ .01. Values at the top of each panel show the number of channels,out of 128, meeting the significance criterion within each interval.



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Figure 8.Independent Component Analysis to remove the iSSP related signal. A. Distribution of mixingweights for the component with the largest iSSP related gamma band spectral perturbation ofband power. B. iSSP waveform in the independent component with the largest perisaccadicperturbation (shown for each of the five patients). For both A and B the units of componentsand weights returned by ICA are arbitrary and have therefore been normalized within eachsubject to the maximum weight across all channels in the former case and to the peak-to-troughdifference in the latter. C. Decrease in perisaccadic 20–200 Hz log spectral perturbation forthe channel with the largest iSSP after removing the kth sorted IC component (sorted byperisaccadic perturbation), normalized for each subject (different colors) to log change afterremoving the first component.



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Figure 9.Effect of ICA filtering (rows) and bipolar rereferencing (columns) on iSSP peak-to-troughamplitude. Data in the left column are in the original common reference space. In the rightcolumn, data have been rereferenced to neighboring contacts within at most 1 cm, indicatedby elongated bars. The top row shows amplitude without ICA filtering, the second row afterremoving the first sorted independent component, and the third row after removing the firstand second sorted independent component. Contacts for which the response does not reachsignificance threshold of FDR q = 0.01 are unfilled.



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Figure 10.Contribution of the filtered components to trial onset related 70–100Hz band-response. A.Mean log band power increase (dB) in the 0 –500 ms epoch after stimulus onset, normalizedto the −400 to −100 ms epoch. Channels for which significance didn’t reach a threshold ofFDR q = 0.01 are unfilled. B. Response after ICA filtering. C. Summary of significance testsin A and B: contacts are colored green if the response remains significant (FDR q = 0.01) beforeand after filtering, red if the response is significant only before filtering but not after, and blueif the response is significant after filtering but not before. D. Contribution of filteredindependent components to trial onset response log power, measured as the decibel log-ratioof power in the 0–500 ms epoch between ICA filtered and unfiltering data. E. Average logband power for the entire duration of the trial in selected channels, before ICA filtering (red)and after filtering (blue). Selected channels are from temporal pole (TP), mesial ventraltemporal cortex, middle section (MVTM), lateral ventral temporal cortex, middle section(MVTL) and posterior ventral temporal cortex (PVT). Time points when the differencebetween the unfiltered and filtered response is significant (FDR q = 0.01) are shown by thickblack line segments along the x-axis.



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Figure 11.Effect of ICA filtering on trial onset responses in depth recordings. The change in 70–100Hzpower following task onset, normalized to respective filtered and unfiltered baselines, is shownfor the common reference (A) and after nearest-neighbor rereferencing (B). The contributionsof filtered components to signal power (log ratio of power without normalizing to baselines,as in Fig. 10D) following trial onset are shown in C and D.



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Figure 12.Log power wavelet spectrograms showing average trial onset related spectral perturbation attemporal pole (contact TP, labeled in figure 10), mesial ventral temporal cortex (contactMVTM), middle section, and posterior ventral temporal cortex (PVT). Thick black linesindicate significance regions for FDR q = 0.001 and thin black lines for q = 0.05. Left columnshows response before ICA filtering, middle column after filtering, and right column showsthe difference of the two. The top left panel shows the histogram of saccade onsets within 50ms bins.



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Figure 13.Log power wavelet spectrograms showing average saccade related spectral perturbation(averaged with respect to saccade onsets detected by eye tracker) for the same contacts as inFigure 10 and 12. Power is normalized to the −500 – −200 ms epoch preceding saccade onset.Thick black lines indicate significance regions for FDR q = 0.001 and thin black lines for q =0.05. Left column shows response before ICA filtering, middle column after filtering, and rightcolumn shows the difference of the two. The top left panel shows the histogram of saccadeonsets within 5 ms bins. The post-saccadic refractory period following the previous saccade,falling within the preceding fixation, is shown (green line), as well as the perisaccadic window(red line).



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Figure 14.An example of similarity in the time course of oEMG related responses and cortical response.Trial onset related increase in 70–100 Hz band power in the temporal pole (contact TP, green)are closely associated with eye movements, while the response observed in posterior ventraltemporal contacts is not (PVT, magenta). A: Both responses have a similar time-courseincluding a peak at 240 ms, as well as magnitude with respect to baseline. Contacts adjacentto PVT (gray and black) also show a similar pattern, although with different amplitudes andlatencies in the initial peak. B: Sorting trials by the delay to the first saccade reveals that theresponse is strongly time-locked to saccade onset (black line) in TP (top) but not in PVT



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(bottom). The data were smoothed over trials with a five point moving average applied aftersorting.



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Figure 15.Perisaccadic changes in interchannel coherence caused by oEMG contamination. Change inmean 70 – 100 Hz interchannel coherence between the saccade-onset window (100 ms centeredat the saccade onset; red bar in Figure 13) and a preceding reference period (preceding 100ms;green bar in Figure 13) in the original data (A), after bipolar rereferencing (B), and after ICAfiltering (C). Saccade onset associated change in coherence pooled across all channels andsubjects. D. The histograms for mean coherence between 40 and 100 Hz in the presaccadic(green) and saccade onset (red) windows. E. The difference between the histogram ofcoherences over all channels and subjects broken down by frequency. A difference is visuallymost apparent between 40 and 100 Hz (bracket on the right side) and is confirmed by a onetailed rank sum test on the medians. The grayscale bar at left shows the result of a one-tailedrank sum test; frequencies at which median coherence in the saccade onset windowsignificantly exceeds that of the presaccadic window at uncorrected P < .001 are tagged whiteand are tagged gray for P < .05.



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